Big Data Equals Big Customer Engagement

“Big data” is all the rage for good reason, as it can potentially deliver the insights that companies need to differentiate themselves in a hyper-competitive business landscape. But having big data is like having big muscles. You might look good, but unless you know how to use your muscles properly, they’re just taking up space and energy.

Successful demonstrations of the power of big data in action are in markedly short supply, and certain studies show that this may be due to a lack of direction regarding where and how to specifically apply data-driven insights. Of course every company has to examine its own priorities to decide where to apply a big data strategy -- or so conventional wisdom says. I think the answer is much simpler. All companies share a common denominator: customers. And as consumer technology has placed unprecedented power at their fingertips, all organizations, regardless of what they produce, have to make customer engagement their number one priority.

As you look for where to kick off your first big data use case, look no further than CRM. In particular, look to big data to provide the information that enables your employees to capitalize on “customer moments,” or customer/organization interactions. As my colleague Glen Stoffel explained recently, customer engagement is the “accumulation of successful customer moments.” What organizations need to ask is, how do we equip our employees to seize the moment and take the best action possible. This is done by “improving our employees’ ability to serve up the right insight (analytic maturity) at the right time (delivered in context via mobile).”

In understanding how a big data strategy must support customer moments, it’s helpful to look at what unsuccessful customer moments look like. Have you ever gotten a call from a company with whom you already do business, where the representative treats you like a new prospect, like a complete stranger? That is a blatantly unsuccessful customer moment.

Despite the fact that we have more data than ever before about our customers, our interactions with them are often as clumsy and awkward as ever. There’s some evidence that CEOs are aware of this -- according to IBM, 90% rate customer engagement as top priority. Yet, heavy investment in big data analytics has yet to meaningfully pay off.

Much of this disconnect is rooted in the way many organizations view data. According to Glen: “...data is not merely numbers; it’s in fact an aggregated collection of personal customer moments...Big data simply speaks a different language...of regression analysis, degrees of significance, factors, equations, demographics, coordinates, price elasticity, and so forth.”

While the “rhetoric of big data” must be used to discern patterns, it’s not useful to most customer facing employees in its raw form, and must be translated into more practical, actionable terms. For example, when your employee is on the phone with a customer, and the data identifies “a significant correlation between relative price differential, call handle time and customer attrition,” what are they supposed to make of it? What you really want the employee to know is that the when this customer doesn’t feel like they’re getting a fair price and their time is being wasted, they’ll leave you and go to a competitor.

But, it’s not enough that your employee understand that -- they’ve got to know, in the moment, how to diffuse the situation. Your CRM has to prioritize the customer, move them up the call queue, and recommend that the employee say something like: “We noticed upon review of your account that you’re up for renewal. Upon pricing review, you’ve qualified to lock in your current rate for another year!”

If you treat customer moments in the same manner that you address data, you receive just that: columns and rows of data... The ultimate goal is to capitalize on opportunities with your insights...it’s all about the action you take to improve that customer moment.

Eric Berridge is co-founder of the global business consulting firm Bluewolf.

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Some very good points Eric. Having spent the past 6 years deeply embedded in Big Data with governments on public policy and international relations issues and global mining companies, the biggest challenge was senior management. The concept of "Big Data" has come to be a bit overworked now and the C-Suite has gone from highly skpetical to expecting miracles, ones the technology can't provide. People are the best analysts, but along the lines of what you've said, few are empowered and are frightened to be because the insights they find may have a bigger impact on the company than they want to be accountable for.